Srinivasan Arunachalam

Peter Hess

Mariana Rajado Silva

Arkopal Dutt

Hari Krovi

Rik Sengupta

Mike Murphy

Robert Davis

Kaoutar El Maghraoui

Ryan Mandelbaum

Research

Technical note

Q & A

Explainer

The fast Fourier transform, how and why it works

What happens when information theory accounts for reasoning?

Demonstrating a theoretical separation between quantum computers and large language models

A new IBM Research specialization teaches how AI models run on modern accelerators

How IBM is searching for quantum advantage in differential equations

A new playbook for quantum optimization benchmarking

How Zurich is shaping the future of algorithms, 70 years in

Generative AI

Mathematical Sciences

Exploratory Science

Quantum Algorithms

Computer Science

Algorithms

Partial Differential Equations

Optimization

Science

Quantum

AI Hardware

Technology impacts every aspect of our work and lives. It is imperative that technology is built responsibly to reduce differential effects on various populations. At IBM Research, we are working to ensure that the technologies we create promote beneficial outcomes for our clients and for the world.

Responsible Technology

IBM has been at the forefront of computer science research since the field’s inception. Our research today focuses on achieving breakthroughs in automation, information processing, and computation. Our goal is to complement and extend human performance — and advance society as a whole. 

We’re working on automation, information processing, and computation research to complement and extend human performance and advance society.

Our long history of research has had an enduring impact on computer science, operations research, and information theory. We’re currently focused on optimization, probability, complexity, geometry of data, as well as linear and multi-linear algebra, to deliver tools that are fundamental to big data and AI.

We’re focused on foundational mathematical research with the aim of delivering tools to that are fundamental to big data and AI.

Our physical sciences researchers seek to understand materials and their properties through advanced characterization methods, explore novel devices and materials for new computational platforms, and apply physics to improve AI algorithms and interpretability.



Physical Sciences

We’re using physics to improve AI algorithms and interpretability, as well as novel materials for new computational platforms. 


Our researchers seek to answer some of the most fundamental questions. We strive for a greater understanding of how our world works and how we can harness that knowledge to advance science, mathematics, and computation.

Exploratory Science

Our work

How Zurich is shaping the future of algorithms, 70 years in

A new IBM Research specialization teaches how AI models run on modern accelerators

Demonstrating a theoretical separation between quantum computers and large language models

What happens when information theory accounts for reasoning?

How IBM is searching for quantum advantage in differential equations

A new playbook for quantum optimization benchmarking

Topics

Computer Science

Mathematical Sciences

Physical Sciences

Responsible Technology

Publications

Shape-Stable Dynamic Control Flow in PyTorch CUDA Graphs

Train More with Less: Fewer GPUs, Less Data Movement, Better Cluster Utilization

Computing the Greatest Common Divisor of Binomial Coefficients binomial(mn,mk)

Observation of a supersolid phase in a spin-orbit coupled exciton-polariton Bose-Einstein condensate

From Fragments to Drugs: How AI and In Silico Methods Accelerate Fragment-to-Lead Optimization

SQISign on ARM